On 11/01/2012 03:43 PM, paul.czodrow...@merckgroup.com wrote:
Dear RDKitters,
> > However, I found it strange that "X_train.shape" gives (373, 177) -
> > shouldn't be the second bit be the number of classes, i.e. 2?
>
> [snip]
>
> > 177 corresponds, BTW, to the number of features..
>
> And that
Dear RDKitters,
> > However, I found it strange that "X_train.shape" gives (373, 177) -
> > shouldn't be the second bit be the number of classes, i.e. 2?
>
> [snip]
>
> > 177 corresponds, BTW, to the number of features..
>
> And that's exactly what this is supposed to represent. The number of
2012/11/1 :
> I was trying to do a train/test set split:
> from sklearn.cross_validation import train_test_split
> X_train, X_test, y_train, y_test = train_test_split(dataDescrs,
> data_activities, test_size=.4)
>
> However, I found it strange that "X_train.shape" gives (373, 177) -
> shouldn't be
> > given a list of of features - e.g. dataDescrs[0] = (140.0, 2, 0.5 -
and a
> > list of experimental observations - e.g. data_activities[0] = 0 - how
do I
> > transform these lists to the scikit-learn nomenclature?
>
> Depends on what these things represent, but if all tuples in
> dataDescrs h
2012/11/1 :
> given a list of of features - e.g. dataDescrs[0] = (140.0, 2, 0.5 - and a
> list of experimental observations - e.g. data_activities[0] = 0 - how do I
> transform these lists to the scikit-learn nomenclature?
Depends on what these things represent, but if all tuples in
dataDescrs ha
Dear Scikitters,
given a list of of features - e.g. dataDescrs[0] = (140.0, 2, 0.5 - and a
list of experimental observations - e.g. data_activities[0] = 0 - how do I
transform these lists to the scikit-learn nomenclature?
Cheers & Thanks,
Paul
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